Artificial Neural Network Modeling of Hydrogen-rich Syngas Production from Methane Dry Reforming over Novel Ni/CaFe2O4 Catalysts

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Artificial Neural Network Modeling of Hydrogen-rich Syngas Production from Methane Dry Reforming over Novel Ni/CaFe2O4 Catalysts

In this study, the application of artificial neural networks (ANN) for the modeling of hydrogen-rich syngas produced from methane dry reforming over Ni/CaFe2O4 catalysts was investigated. Multi-layer perceptron (MLP) and radial basis function (RBF) neural network architectures were employed for the...

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Bibliographic Details
Main Authors:	Hossain, M. Anwar, Ayodele, Bamidele V., Cheng, C. K., Khan, Maksudur R.
Format:	Article
Language:	English
Published:	Elsevier Ltd 2016
Subjects:	TP Chemical technology
Online Access:	http://umpir.ump.edu.my/id/eprint/13179/ http://umpir.ump.edu.my/id/eprint/13179/1/Artificial%20Neural%20Network%20Modeling%20Of%20Hydrogen-Rich%20Syngas%20Production%20From%20Methane%20Dry%20Reforming%20Over%20Novel%20Ni-CaFe2O4catalysts.pdf

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